Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Dávid Gajdoš"'
Autor:
'Ľubomír Antoni, Erik Bruoth, Alexander Szabari, Gabriela Vozáriková, Peter Bugata, Peter Bugata Jr, Dávid Gajdoš, Dávid Hudák, Vladimíra Kmečová, Monika Staňková\\'
Publikováno v:
Computing in Cardiology Conference (CinC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3bf147c627390c76514437fc628b0fbb
https://doi.org/10.22489/cinc.2022.067
https://doi.org/10.22489/cinc.2022.067
Autor:
Lubomir Antoni, Erik Bruoth, Peter Bugata, Dávid Gajdoš, Šimon Horvát, Dávid Hudák, Vladimíra Kmečová, Richard Staňa, Monika Staňková, Alexander Szabari, Gabriela Vozáriková
Publikováno v:
Artificial Intelligence in Medicine ISBN: 9783031093418
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aaf0c83255063788e39969bae63fc967
https://doi.org/10.1007/978-3-031-09342-5_42
https://doi.org/10.1007/978-3-031-09342-5_42
Autor:
Ľubomír Antoni, Erik Bruoth, Peter Bugata, Peter Bugata Jr, Dávid Gajdoš, Šimon Horvát, Dávid Hudák, Vladimíra Kmečová, Richard Staňa, Monika Staňková, Alexander Szabari, Gabriela Vozáriková
Publikováno v:
Physiological Measurement. 43:064008
Objective. Within the PhysioNet/Computing in Cardiology Challenge 2021, we focused on the design of a machine learning algorithm to identify cardiac abnormalities from electrocardiogram recordings (ECGs) with a various number of leads and to assess t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::58a5caa21625a7bcf89fa9ca9c096b07
https://doi.org/10.1088/1361-6579/ac69a8
https://doi.org/10.1088/1361-6579/ac69a8